The challenge of accurate software project status reporting: a two-stage model incorporating status errors and reporting bias

Software project managers perceive and report project status. Recognizing that their status perceptions might be wrong and that they may not faithfully report what they believe, leads to a natural question-how different is true software project status from reported status? Here, the authors construct a two-stage model which accounts for project manager errors in perception and bias that might be applied before reporting status to executives. They call the combined effect of errors in perception and bias, project status distortion . The probabilistic model has roots in information theory and uses discrete project status from traffic light reporting. The true statuses of projects of varying risk were elicited from a panel of five experts and formed the model input. The same experts estimated the frequency with which project managers make status errors, while the authors created different bias scenarios in order to investigate the impact of different bias levels. The true status estimates, error estimates, and bias levels allow calculation of perceived and reported status. The results indicate that at the early stage of the development process most software projects are already in trouble, that project managers are overly optimistic in their perceptions, and that executives receive status reports very different from reality, depending on the risk level of the project and the amount of bias applied by the project manager. Key findings suggest that executives should be skeptical of favorable status reports and that for higher risk projects executives should concentrate on decreasing bias if they are to improve the accuracy of project reporting.